Abstract Rationale Macrophages are the predominant immune cells in Chronic Obstructive Pulmonary Disease (COPD). Due to their larger size and increased granularity, particularly after cigarette smoke (CS) exposure, these cells exhibit high levels of autofluorescence, which poses a major challenge for conventional flow cytometry (CFC). Autofluorescence can overlap with fluorochrome emission spectra, compromising the accurate detection of specific cellular markers. Spectral flow cytometry (SFC) addresses this limitation by distinguishing and subtracting autofluorescent spectra from true fluorescence signals emitted by antibody-labeled cell markers, thereby enhancing the resolution of distinct cell populations. This study aimed to evaluate the impact of autofluorescence in a CS-induced COPD mouse model by comparing SFC and CFC. Methods Male C57BL/6 mice were exposed to either filtered air (n = 4) or CS (n = 4) for four weeks. Pulmonary inflammation was assessed in bronchoalveolar lavage (BAL) fluid and lung tissue using paired SFC and CFC analyses. Results Spectral unmixing of autofluorescence using SFC improved resolution and resulted in more reliable FMOs to gate immune cell populations compared to SFC without autofluorescence unmixing and CFC. In BAL samples, CFC significantly overestimated macrophage frequency and underestimated neutrophils and dendritic cells compared with SFC in both air- and smoke-exposed mice. The same trend was observed for macrophages and dendritic cells in lung tissue. Notably, this discrepancy was minimal when autofluorescence unmixing was omitted in SFC. Conclusion These findings demonstrate that managing autofluorescence by spectral flow cytometry provides more sensitive and accurate pulmonary immune cell characterization in CS-induced COPD models. This abstract is funded by: None
Geirnaert et al. (Fri,) studied this question.